Increasing Soil Nutrients Availability and Sustainability by ...article.aascit.org/file/pdf/8050014.pdfgrowth. Glomalin is a mycorrhizal glycoprotein produced in soil with the ability

International Journal of Agricultural and Biosystems Engineering

2017; 2(6): 74-84

http://www.aascit.org/journal/ijabe

Keywords Alkaline Soils,

Glomalin-Related Soil Protein,

Sustainable Management,

GRSP-Bound Metals,

Micronutrients,

Nutrients Availability

Received: September 4, 2017

Accepted: November 22, 2017

Published: December 23, 2017

Increasing Soil Nutrients Availability and Sustainability by Glomalin in Alkaline Soils

Mohamed Emran1, *

, Mohamed Rashad1, Maria Gispert

2,

Giovanni Pardini2

1Land and Water Technologies Department, Arid Lands Cultivation Research Institute (ALCRI),

City of Scientific Research and Technological Applications (SRTA-City), New Borg El-Arab

City, Alexandria, Egypt 2Soil Science Unit, University of Girona, Girona, Spain

Email address [email protected] (M. Emran) *Corresponding author

Citation Mohamed Emran, Mohamed Rashad, Maria Gispert, Giovanni Pardini. Increasing Soil Nutrients

Availability and Sustainability by Glomalin in Alkaline Soils. International Journal of

Agricultural and Biosystems Engineering. Vol. 2, No. 6, 2017, pp. 74-84.

Abstract Alkaline soils in arid areas frequently have low-nutrient contents available for plant

growth. Glomalin is a mycorrhizal glycoprotein produced in soil with the ability to

sequester soil nutrients thereby increasing their availability according to the soil-

ecological conditions. The study area has been selected to cover two different agro-

ecological areas (coastal region: S1-S7 and S13-S16; Eastern Delta region: S8-S12).

Within these areas, sixteen agricultural fields were selected with various soil textures,

different water resources, appropriateness of the drainage system, manure addition, crop

rotation and plant cover at sampling. Soil texture, pH, electrical conductivity (EC), soil

organic carbon (SOC), easily extractable glomalin-related soil protein (EEGRSP) and

total glomalin (TGRSP) contents were analysed. Soil micronutrients (Fe, Zn, Mn and

Cu) and potentially toxic metals (Cd, Pb, Co, Ni and Cr) were measured in soil and in

each extraction cycle of glomalin. Organic carbon in the GRSP extraction solutions

amounted by 26-30% in all soils. One-way ANOVA showed significant differences

(p<0.05) between the studied soils demonstrating the effects of agro-ecological

differences on soil ecosystems. All soils showed wide range concentrations of metal ions

bound to glomalin. The GRSP-bound metals were FeGRSP (0.04-1.16 mg kg–1

), ZnGRSP

(0.69 mg kg–1

only in S4), MnGRSP (9.52-105.16 mg kg–1

), CuGRSP (1.05-5.01 mg kg–1

)

NiGRSP (0-0.23 mg kg–1

) and PbGRSP (2.70-3.26 mg kg–1

) and highly found in S4 and S8-

S12 soils intercropped with legumes and annually received manure addition. The

cumulative increase of these metals observed along the sequential extraction of GRSP

may indicate the ability of glomalin for increasing their availability and sustainability

during its persistence in soil. Factor analysis explained 41% of total variance in the 1st

Factor with high positive loadings from silt, clay, SOC, TGRSP, Fe, Mn, Cu, Ni, Cr,

FeGRSP, MnGRSP and PbGRSP. Factor 2 with 21% of total variance was positively correlated

with EEGRSP, Zn, Cu, Cd, Pb, FeGRSP, CuGRSP and PbGRSP. These findings illustrate the

capacity of glomalin to bind metals for increasing their availability to plant growth and,

in addition, alleviate the effects of toxic metals depending on the appropriateness of

drainage system, manure additions, crop rotation and changes in plant cover. As a result,

glomalin can be used as a biofertilizer for sustainable agricultural management to help

manage soil nutrients sustainability. It can be also used as a phytoremediator to recover

toxic metals in polluted soils.

75 Mohamed Emran et al.: Increasing Soil Nutrients Availability and Sustainability by Glomalin in Alkaline Soils

1. Introduction

Agricultural areas in Egypt are concentrated in the Nile

delta and have recently been extended to marginal areas at

the East and West of the Delta region and the Northern

coastal region. All these regions are characterized by alluvial

alkaline soils with high CaCO3 and classified as salt-affected

soils due to high salinity risks. These alluvial soils were

formed from the deposition of organo-mineral materials

during the flooding seasons for thousands of years before the

construction of Aswan Dam [1]-[3]. The soils are extremely

fertile with loamy texture due to the abundance of organic

matter and minerals [4]. At the marginal areas and

particularly in the northern coastal region, calcareous soils

are predominated and affected by a Mediterranean climate.

These areas often receive animal manure and are planted

with legumes and Alfalfa to provide the soil with

mycorrhizae and nitrogen-fixing bacteria [5]-[6]. This type of

soil agricultural management allows these newly reclaimed

areas to increase their fertility conditions within three to five

years which cannot be achieved under any other system. It

may also provide a complete nutrient source containing soil

macro and micronutrients thus promoting soil biological

activity and consequently improving soil structure.

In arid areas soils are characterized by low nutrients

contents and the majority of plants tend to improve nutrient

uptake through symbiotic associations with soil microbes,

including fungi, that have the ability to resist desiccation and

drought [7]. Thus plants develop strategies to grow under a

variety of stressful conditions [8]. The major fungal group

found in the roots of 80% of terrestrial plant species is the

arbuscular mycorrhizal fungi (AMF). AMF live in

mutualistic symbiotic associations with host plants,

increasing nutrient uptake thus enhancing plant productivity.

AMF produce a glycoprotein in soil known as ‘’glomalin’’.

Glomalin is operationally identified as glomalin-related soil

protein (GRSP) totally extracted by sequential extractions

using sodium citrate (pH 8.0) at 121°C [9], [10], [11]. It

contributes to the formation of stable soil aggregates [12].

Increased soil aggregates stability may protect adsorbed

nutrients within soil aggregates [13]. Moreover, soil

aggregates increase the potential of metal nutrients

sustainability and the exchangeable cations and

micronutrients they contain may be good indicators of soil

health. Therefore, glomalin can be considered as a stabilizing

agent, in the formation of soil aggregates, and a binding

agent of soil minerals promoting the formation of organo-

mineral complexes [10], [14]. Many studies have shown high

variability in cations bound to GRSP among different soils

[15]-[16]. In addition, GRSP showed a high potential

sequestration capacity for Pb, Cd, Zn, Cu, Fe and Mn thus

influencing their mobility in the soil [16]-[18].

This work aimed to identify the capacity of GRSP to

sequester metal ions in alkaline soils subjected to different

agricultural practices. GRSP-bound metals were measured in

the sequential extractants of GRSP to provide a direct

evaluation of soil nutrients and toxic metals adsorbed to

glomalin and their sustainability under different soil

management practices.

2. Materials and Methods

2.1. Study Area and Sampling

The study area has an arid Mediterranean climate with

temperature ranges from 8-25°C in winter and around 30-36°C

in summer. The study area is including sixteen agricultural

fields (S1-S16) of alkaline soils subjected to different

agricultural practices. It covers two agro-ecological zones;

Coastal region (S1-S7 and S13-S14) and Eastern Delta region

(S8-S12). The study area is typical for the extensive flood

plains in the Nile River Delta region. The potential evaporation

rate is 1,500 mm year–1

with low precipitation (~120 mm year–

1). The studied soils have been selected to represent different

sampling sites with various soil textures, water resources,

appropriateness of drainage system, frequent manure

applications, crop rotation system intercropped with legumes

and current cultivation at sampling. The current cultivation of

each site is recorded in Table 1. The major crops are rice,

wheat, barley, corn, clover and cotton and sometimes

intercropped with legumes and alfalfa. Surface irrigation is the

common system used in all sites. The water table is shallow at

2.5-4 m depth thus producing salt-affected soils [19].

In the coastal region, soils (S1-S7 and S13-S16) are

generally irrigated by Nile water coming from El-Nasr canal

supplied by El-Noubariya canal. The S13-S16 soils are

occasionally irrigated by moderately saline water

(groundwater). Soils are located in New Borg El-Arab city

(Alexandria Governorate) and are colluvial calcareous

alkaline soils classified as Typic Calciorthids according to the

Soil Association Map of Egypt [20]-[21]. At the Eastern

Delta region, soils (S8-S12) are located in El-Hawaber

village, Diarb Nigm city (El-Sharkia governorate) and are

alluvial alkaline soils classified as Vertic Torrifluvents, the

prevalent soil characteristic of the Egyptian Nile River Delta.

These soils are generally irrigated by Nile water comes from

Damietta branch with a total dissolved salts (TDS) of 400-

600 mg L-1

.

Soils were sampled in triplicate at each site and combined

to obtain a representative soil sample. Coordinates of each

site can be seen in Table 1. Samples collected from the upper

30 cm depth of the A-horizon. The first site (S1) represents a

soil without any agricultural management (bare soil) with a

loamy sand texture. Other soils at S2-S6 are sandy loam and

soils at S7-S16 are sandy clay loam. Soils at S8-S12 receive a

manure application annually and do not have an appropriate

drainage system leading to salt accumulation in the upper

surface layers.

2.2. Experimental Analyses

2.2.1. Soil Analysis

All soils were air-dried, ground and sieved at 2 mm.

International Journal of Agricultural and Biosystems Engineering 2017; 2(6): 74-84 76

Particle size analysis was determined using Hydrometer with

Bouyoucos scale in g L–1

. Soil pH and electrical conductivity

(EC) were measured in 1:1 (w/v) aqueous soil suspension.

Soil organic carbon (SOC) was determined using dichromate

oxidation method. Soil micronutrients such as Fe, Zn, Mn

and Cu and potentially toxic metals including Cd, Pb, Cr, Ni

and Co were extracted in diethylenetriaminpenta acetic acid

(DTPA) solution [22] then quantified by the Agilent 4100

Microwave Plasma-Atomic Emission Spectrometer (MP-

AES) (USA).

Glomalin was extracted in 20 mM trisodium citrate (pH

7.0) at 121°C for 30 min to represent the labile fraction (F1;

first fraction) that is hereafter named the easily extractable

glomalin-related soil protein (EEGRSP). Sequential

extraction autoclave cycles were performed to obtain the

other 10 fractions (F2-F11) using 50 mM trisodium citrate

(pH 8.0) at 121°C for 30 min [10], [11], [13], [23]. The total

extractable glomalin-related soil proteins (TGRSP)

represented the sum of all fractions. All glomalin fractions

were separately quantified by using the Bradford protein

assay [11], [24]. Contents of micronutrients (Fe, Zn, Mn and

Cu) and toxic metals (Cd, Pb, Co, Ni and Cr) in each fraction

and in the TGRSP (representative sample) were quantified by

the Agilent 4100 Microwave Plasma-Atomic Emission

Spectrometer (MP-AES) (USA). Carbon in each glomalin

fraction (G-C) was detected using the TOC Analyser (Torch

Combustion TOC/TN Analyzer - Teledyne Tekmar, Ohio,

USA) and expressed as a percentage.

2.2.2. Statistical Analysis

All data, previously standardized, were statistically

analysed using STATISTICA 10 of StatSoft, Inc. [25] (Tulsa,

Oklahoma, USA). One-way ANOVA was checked for the

studied soil parameters. Pearson correlation was checked for

all measured soil parameters. Factor analysis was run to

reduce and classify variables (soil properties). The first three

factor structures explained the most significant variance

within the variables (soil properties). Moreover, factor

analysis provided factor score values to explore the

relationships between the variables (soil parameters) and the

16 soils to obtain a picture of the overall dynamics.

3. Results and Discussion

3.1. General Soil Physico-Chemical

Characteristics

All soils were moderately alkaline conditions within a pH

range of 7.5 to 8.5 (Table 1). Using the one-way ANOVA,

high significant variability (p<0.05), indicated by letters from

a-c, for clay, silt, sand, pH, EC and SOC was observed

among the studied soils reflecting the variations in soil

texture and ecological areas. For example, EC values showed

significant data variability in soils with sandy loam

(mean=1.075±0.81 dS m–1

), sandy clay loam

(mean=4.44±2.31 dS m–1

) and loamy sand

(mean=15.50±0.16 dS m–1

). Soils at S1 can be classified with

very strong salinity risk [26] (>9.5 dS m–1

). Strong salinity

risk (4.8-9.4 dS m–1

) was observed in S9, S11 and S13-S16

due to the inappropriate soil management and high salinity of

water for irrigation in those soils (TDS 3000-4000 mg L–1

)

while moderate salinity (2.5-4.4 dS m–1

) was observed in S4

and S8-S12. Slight salinity risk (1.3-2.4 dS m–1

) was

observed in soil under Alfalfa (Trifolium alexandrinum)

(S10). No salinity risk (<1.2 dS m–1

) was observed in S2-S3

and S5-S7 probably due to the low salt concentrations in the

irrigation water (Table 1). The high SOC contents observed

in S4 and S8-S12 were due to the frequent manure

application. Soils in S8-S12 showed with high salinity and

organic matter contents due to manure addition in soils with

an inappropriate drainage system leading to salt

accumulation and resulted in salt-affected soils. The highly

significant negative correlation was found between soil pH

and electrical conductivity (r=-0.716, p<0.01).

Table 1. Locations Description, Current Plants and General Soil Characteristics of the Studied Soils.

Site Plant Coordinates Sand% Silt% Clay% pH EC (dS m–1) SOC (mg/kg)

S1 Bare soil 30°44'22.22"N 29°28'32.08"E 83.60 b 4.46 ab 11.94 a 7.56±0.03 a 15.50±0.16 c 2.79±0.30 a

S2 Bean 30°44'14.35"N 29°29'26.54"E 75.72 b 5.25 a 19.03 a 8.50±0.06 b 0.66±0.00 a 2.30±0.00 a

S3 Wheat 30°44'20.80"N 29°30'19.64"E 73.09 b 7.88 a 19.03 a 8.43±0.08 b 0.68±0.02 a 3.52±0.35 a

S4 Apple 30°45'30.04"N 29°32'10.67"E 75.72 b 6.56 a 17.72 a 8.04±0.02 b 2.53±0.01 a 10.08±0.35 a

S5 Artichoke 30°45'36.04"N 29°31'8.21"E 73.09 b 7.88 a 19.03 a 8.34±0.07 b 0.76±0.03 a 5.74±0.30 a

S6 Artichoke 30°46'4.86"N 29°30'58.86"E 70.47 b 10.50 a 19.03 a 8.06±0.02 b 0.75±0.00 a 10.33±0.00 a

S7 Alfalfa 30°46'4.99"N 29°32'34.51"E 73.09 a 5.25 c 21.66 b 8.44±0.05 ab 0.57±0.00 b 5.82±0.58 b

S8 Onion 30°43'13.67"N 31°23'45.11"E 57.34 a 18.38 c 24.28 b 7.87±0.04 ab 3.85±0.02 b 15.41±0.23 b

S9 Onion 30°42'58.77"N 31°23'39.50"E 52.09 a 21.00 c 26.91 b 7.85±0.06 ab 6.54±0.20 b 13.93±0.46 b

S10 Alfalfa 30°43'6.18"N 31°24'14.31"E 52.09 a 13.13 c 34.78 b 8.04±0.02 ab 1.73±0.12 b 14.43±0.70 b

S11 Garlic 30°43'0.57"N 31°23'7.02"E 52.09 a 21.00 c 26.91 b 7.76±0.01 ab 8.53±0.08 b 14.84±0.58 b

S12 Lettuce 30°43'22.82"N 31°23'11.40"E 57.34 a 13.13 c 29.53 b 8.02±0.03 ab 3.30±0.03 b 14.75±0.23 b

S13 Alfalfa 30°48'30.97"N 29°31'52.20"E 65.22 a 10.50 bc 24.28 b 7.68±0.06 ab 5.47±0.06 b 5.82±0.58 a

S14 Bean 30°47'5.26"N 29°37'42.13"E 59.96 a 13.13 bc 26.91 b 7.83±0.02 ab 5.03±0.23 b 6.15±0.12 a

S15 Zucchini 30°57'30.64"N 29°42'46.12"E 52.09 a 18.38 bc 29.53 b 8.38±0.04 ab 5.58±0.45 b 7.21±1.62 a

S16 Barley 30°57'3.05"N 29°46'7.43"E 49.46 a 18.38 bc 32.16 b 8.43±0.02 ab 3.77±0.04 b 5.25±0.23 a

EC: Electrical conductivity; CaCO3: Calcium carbonate contents; SOC: Soil organic carbon.

Different letters (a-c) indicate the significant data variability at p<0.05 checked by one-way ANOVA.


3.2. Glomalin as a Reserve of Soil Organic

Carbon

Glomalin is a glycoprotein containing about 15% carbon

and has been shown by many authors to be positively

correlated with SOC pools [10], [11], [13], [23], [27], [28].

Glomalin is considered to be a stabilizing agent binding soil

nutrients and minerals with soil particles in the formation of

organo-mineral complexes and the stabilization of soil

aggregates. These complexes may contribute to soil carbon

storage capacity via the assimilation of atmospheric CO2 by

mycorrhizal plant species. The current study showed a wide

range of soil glomalin contents not only due to the significant

differences in soil texture but also due to differences in plant

species and manure application thus affecting the preservation

of SOC pools [29]. In the 1st graph of Figure 2, the highest

glomalin contents were generally found in the first fraction

(F1) that represent the easily extractable glomalin fraction.

Glomalin then decreased from F1 to F8. The F8 can be

operationally considered as the final fraction containing

glomalin molecules due to the disappearance of the brown

colour in this fraction. The increasing of GRSP values in the

F9 may indicate the reappear of glomalin-like compounds

probably extracted with sodium citrate. In the 2nd

graph of

Figure 2, carbon contents in all glomalin fractions showed low

concentrations (1-2%) in the first fraction (F1) in all soils. The

carbon content in glomalin extraction fractions increased from

F1 to the highest concentrations (4-5%) in the F6 and then

decreased again <1% in the last fraction (F11). This means that

different organic compounds can be found from each fraction

of glomalin indicating the presence of other glomalin-like

compounds probably subjected to different stabilization

mechanisms of organic carbon (G-C) in all soils.

Accordingly, significant positive correlations (p<0.01) were

obtained for the EEGRSP and TGRSP as a function of soil

organic carbon (SOC) contents (Figure 1). The TGRSP contents

were negatively correlated with sand (r=–0.648, p<0.01) while

positively correlated with silt (r=0.498, p<0.05) and clay

(r=0.698, p<0.01). SOC increased significantly with the

EEGRSP (r=0.658, p<0.01) and TGRSP (r=0.846, p<0.01). The

highest concentrations of the easily extractable glomalin

fractions were found in soils under apple (S4) and under

artichoke (S6) in agreement with the highest SOC contents

among sandy loam soils. The highest concentrations of TGRSP

were also found in soils under apple (S4) and soils of S8-S12

due to the high SOC contents because of the intense manure

applications. In addition, intercropping with legumes and Alfalfa

at these soils S8-S12, beside annual manure applications,

promoting the potential preservation of SOC pools to be

stabilized by the beneficial soil microbes such as mycorrhizae

and nitrogen-fixing bacteria. This promotion in the preservation

of organic compounds carried out by soil microbes is owing to

the manure application that provides the soil with a complete

nutrient source for promoting biological activities in the upper

soil layers thus improving soil physical characteristics.

Figure 1. Linear Correlations Between the Easily Extractable (EEGRSP) and Total (TGRSP) Glomalin-Related Soil Protein and Soil Organic Carbon (SOC)

Contents.


Figure 2. Glomalin-Related Soil Protein (GRSP) Concentrations and Glomalin-Carbon (G-C) for Each Extraction Fraction (F1-F11) in All Soils.

3.3. Increasing the Availability of Soil

Micronutrients in Soil

Soil micronutrients varied widely among the studied soils

probably due to manure addition, plant cover and soil texture

(Table 2). Iron (Fe) varied from 0.12 mg kg–1

in the bare soil to

18.08 mg kg–1

in S10 under Alfalfa. Zinc showed very low

values varied within 0.02-7.38 mg kg–1

and notable below the

recommended limit of 50 mg kg–1

as proposed by the WHO

1996 and under 300 mg kg–1

at pH more than 7.0 as proposed

by the Department of Environment [30]. The highest value

was found in S4 under Apple trees probably comes from

agrochemical additions. Zinc was positively correlated with

the easily extracted glomalin fraction (r=0.557, p<0.05).

Manganese also showed a wide range of concentrations among

the studied soils varied from 2.43 mg kg–1

in bare soil (S1) to

the highest value in S10 under Alfalfa. The higher values

(18.18-26.21 mg kg–1

) were found in soils of S8-S12 due to

manure addition. Manganese was positively correlated with silt

(r=0.546, p<0.05) and clay (r=0.674, p<0.01) while negatively

correlated with sand fraction (r=-0.659, p<0.01). Highly

significant correlations were also found between manganese in

soil and SOC (r=0.866, p<0.01) and TGRSP (r=0.836, p<0.01)

contents. Copper (Cu) contents were very low (0.11-2.77 mg

kg–1

), with high concentrations in soils at S8-S12, but contents

remained below the recommended maximum limit of 200 mg

kg–1

at pH >7.0 [30]. Copper concentrations in DTPA

extraction solutions were significantly correlated with SOC

(r=0.768, p<0.01), EEGRSP (r=0.561, p<0.05) and TGRSP

(r=0.807, p<0.01) contents. Nickel, recently recognized to be a

soil micronutrient, was present in low amounts between 0.02-

0.24 mg kg–1

and far below the recommended maximum limit

of 110 mg kg–1

[30] (pH >7.0). Soil micronutrients increased in

soils after manure applications [31]. Nitrogen addition

generally increased the availability of soil micronutrients such

as Fe, Mn and Cu and their availability were pH dependent.

Cadmium content in these soils was very low (0.0004-0.08

mg kg–1

) (Table 2). Lead (Pb) varied from 0.24 mg kg–1

to

4.74 mg kg–1

. These values are very low and did not exceed

the limit of 200 mg kg–1

[30] in soils with a pH >7.0. Cobalt

(Co) and chromium (Cr) concentrations in these soils were

very low and less than 0.06 mg kg–1

and 0.97 mg kg–1

,

respectively.


Table 2. Soil Micronutrients (Fe, Zn, Mn and Cu) and Toxic Metals (Cd, Pb, Co, Ni and Cr) in the Studied Soils.

S1 S2 S3 S4 S5 S6 S7 S8

Fe 0.1170±0.0070 4.8276±0.0162 4.2069±0.0115 5.8842±0.0197 4.0677±0.0070 3.9586±0.0088 4.3982±0.0085 9.4152±0.0435

Zn 0.0245±0.0012 0.2774±0.0019 0.5704±0.0008 7.3774±0.0201 0.5756±0.0026 0.4946±0.0026 0.3113±0.0011 0.9448±0.0029

Mn 2.4322±0.0095 8.6438±0.0300 8.2171±0.0440 10.4976±0.0132 9.0625±0.0187 9.0858±0.0577 9.0622±0.0092 20.1162±0.0231

Cu 0.1106±0.0013 0.2219±0.0012 0.3605±0.0020 2.7683±0.0222 0.3645±0.0029 0.2831±0.0013 0.3566±0.0025 1.9732±0.0206

Cd 0.0017±0.0001 0.0007±0.0012 0.0006±0.0002 0.0846±0.0007 0.0007±0.0006 0.0009±0.0005 0.0004±0.0008 0.0081±0.0004

Pb 0.2431±0.0011 0.6914±0.0011 1.0263±0.0008 4.7367±0.0012 0.6345±0.0005 0.6707±0.0004 0.8363±0.0010 1.6459±0.0014

Co 0.0030±0.0008 0.0391±0.0010 0.0139±0.0008 0.0337±0.0002 0.0020±0.0008 0.0560±0.0007 0.0037±0.0005 0.0002±0.0004

Ni 0.0205±0.0001 0.1489±0.0002 0.1199±0.0005 0.1072±0.0002 0.0944±0.0004 0.1132±0.0006 0.1251±0.0010 0.2437±0.0004

Cr 0.0161±0.0002 0.0115±0.0004 0.0184±0.0001 0.0144±0.0001 0.0071±0.0001 0.0041±0.0004 0.0048±0.0003 0.0838±0.0004

Table 2. Continued.

S9 S10 S11 S12 S13 S14 S15 S16

Fe 0.5857±0.0013 18.0750±0.0943 0.7482±0.0164 12.8909±0.0141 2.3078±0.0243 2.4335±0.0206 2.7508±0.0153 3.3194±0.0192

Zn 0.3905±0.0033 0.4913±0.0018 0.4640±0.0042 0.8621±0.0058 0.4182±0.0009 0.6067±0.0006 0.4448±0.0030 0.4868±0.0017

Mn 16.9731±0.0422 26.2145±0.0309 16.5329±0.0874 18.1809±0.0340 8.0748±0.0052 8.4367±0.0029 8.7072±0.0078 10.2277±0.0050

Cu 1.2732±0.0060 2.5093±0.0182 1.0979±0.0132 2.2152±0.0204 0.3143±0.0019 0.3063±0.0021 0.3415±0.0020 0.3127±0.0021

Cd 0.0130±0.0002 0.0067±0.0008 0.0009±0.0008 0.0037±0.0004 0.0018±0.0005 0.0015±0.0008 0.0012±0.0005 0.0030±0.0007

Pb 0.3392±0.0008 0.5562±0.0005 1.0010±0.0003 2.1031±0.0018 0.9623±0.0011 3.8674±0.0011 1.1095±0.0011 1.0169±0.0011

Co 0.0001±0.0002 0.0002±0.0005 0.0001±0.0001 0.0002±0.0003 0.0008±0.0003 0.0019±0.0006 0.0008±0.0002 0.0002±0.0006

Ni 0.1367±0.0004 0.2353±0.0003 0.1132±0.0003 0.2418±0.0009 0.0851±0.0003 0.0948±0.0006 0.0985±0.0005 0.1403±0.0003

Cr 0.2953±0.0006 0.9722±0.0044 0.0097±0.0002 0.6473±0.0007 0.0091±0.0001 0.0079±0.0001 0.0205±0.0001 0.0182±0.0001

3.4. GRSP-Bound Metals

GRSP has been recently considered as the most important

fraction of SOM for its contribution to soil macro nutrients

such as soil organic carbon, nitrogen and phosphorus. It also

has the important ability to bind metals and so to sequester

soil micronutrients such as Fe, Zn, Mn and Cu thus

increasing their availability in soil [15], [17], [18]. In

addition, glomalin tends to bind with toxic metals thus may

alleviate their adverse effects in soils depending on the

differences in metal chemistry [32]. Our results showed high

significant variability in the metal sequestration capacity of

glomalin among the studied soils. The highest values of iron

(FeGRSP), manganese (MnGRSP), copper (CuGRSP) and lead

(PbGRSP) in GRSP extraction solutions were observed in S4

and S8-S12 (Figure 3). It can be also observed that the higher

values were generally found in the first extraction fraction

(F1) that represented the easily extractable glomalin fraction.

In Figure 3, the Fe, Mn and Cu showed almost the same trend

along the sequential extraction fractions from F1 to F11. The

total sum of metal ions for all fractions (F1-F11) extracted by

sodium citrate along the sequential extractions may have

released more ions bound to other soil fractions such as

glomalin-like compounds. These other soil fractions resulted

in the ninth fraction (F9) when the GRSP values increased

again in all soils despite the absence of brown colour in the

extraction solution. Lead showed the same trend in the first 6

fractions despite its absence in the F7. The one-way ANOVA

showed significant variations among all fractions from F1 to

F11 for iron, manganese and copper (Table 3).

In Table 4, the highly significant positive correlation found

between Fe in soil and TGRSP (r=0.692, p<0.01) probably

indicating the stabilization of glomalin by binding with iron

in soils with high iron contents [16], [27]. This hypothesis

was confirmed through the significant positive correlations

between iron in GRSP extraction solution (FeGRSP) and

EEGRSP (r=0.588, p<0.05), TGRSP (r=0.778, p<0.01) and

soil organic matter (SOM) (r=0.697, p<0.01) contents.

Accordingly, iron can bind with the easily glomalin fraction

(EEGRSP) and its recalcitrance/stable form increased

relatively with the stabilization of organic compounds in soil.

Manganese in GRSP extraction solutions found to be

positively correlated with silt (r=0.546, p<0.05) and clay

(r=0.530, p<0.05) while negatively correlated with the sand

fraction (r=-0.581, p<0.05). Highly significant positive

correlations were also found between manganese (MnGRSP)

and SOC (r=0.854, p<0.01) and TGRSP (r=0.728, p<0.01)

contents (Table 4). Copper (CuGRSP) was positively correlated

with the easily glomalin fraction (r=0.666, p<0.01) and total

glomalin (r=0.559, p<0.05) (Table 4). Nickel is recently

added to leguminous crops in the soil as a micronutrient for

its role in nitrogen fixation and nodulations. The excessive

addition of Zn and Cu in soil with alkaline conditions may

cause a Ni deficiency [33]. Consequently, the highest Ni

concentration observed in GRSP extraction solution was

found in S2 under bean because Ni deficiency was treated by

adding Ni in its water-soluble form as a foliar spraying

(water-soluble Ni fertilizer). Lead showed high values in S4

and S8-S12 corroborating the role of glomalin in the

immobilization of Pb thus lowering its toxicity in soils with

high pH values [17]. A significant positive correlation was

found between TGRSP and PbGRSP (r=0.739, p<0.01).

The GRSP-bound metals (FeGRSP, MnGRSP, CuGRSP and

PbGRSP) showed high ratios when compared to their contents

in soil. Each metal showed a wide range ratio as iron

(FeGRSP/Fesoil) ranged from zero to one ratio, Mn

(MnGRSP/Mnsoil) from 1.0 to 4.4 ratio, Cu (CuGRSP/Cusoil) from

0.8 to 10.5 ratio, Pb (PbGRSP/Pbsoil) from 0.7 to 12.0 ratio and

Ni (NiGRSP/Nisoil) from zero to 1.5 ratio. These metals

decreased significantly with their contents in soil as can be

indicated by the following negative power equations: Fe


(y=0.18x-0.46

, r=-0.65, p<0.01), Mn (y=9.85x-0.91

, r=-0.88,

p<0.01), Cu (y=1.85x-0.63

, r=-0.94, p<0.01) and Pb (y=3.04x-

0.99, r=-0.99, p<0.01). These correlations may indicate the

potential sequestration capacity of glomalin to bind metals.

The higher adsorption capacity was found in soils at S4 and

S8-S12 than other soils because of the high SOM and

glomalin contents. Nickel did not show any significant

relationships because of the very low quantities in soil and

therefore in GRSP extracts.

After logarithmic transformation of the ratio of metal

content in GRSP and in soil, clear trends were observed for

iron, manganese and copper in some soils such as S4 and S8-

S12 indicating their capacity for sequestering these nutrients.

Highly significant correlations of logarithm transformed were

ratios of iron (FeGRSP), manganese (MnGRSP), copper (CuGRSP)

and lead (PbGRSP) in GRSP extraction solutions as a function

of their soil contents (y-axis) against the logarithmic

transformation of their contents in soil (x-axis) (Figure 4). No

significant correlation was found for NiGRSP.

Table 3. One-way ANOVA of Fe, Mn and Cu in all Glomalin Fractions (F1-F11) Extracted from the Studied Soils.

Nutrient Source of Variation SS df MS F P-value

Fe

Between Groups 5826 15 388.40 2.28 0.00638700

Within Groups 24537 144 170.40

Total 30363 159

Mn

Between Groups 12536 15 835.75 5.43 0.00000001


Total 36850 173

Cu

Between Groups 7 15 0.46 3.36 0.00006343


Total 28 174

Figure 3. Concentrations of Fe, Mn, Cu and Pb in each Operational Fraction of GRSP.


Figure 4. Linear Correlations Between Log Transformations of GRSP-Bound Metals (FeGRSP/Fesoil, MnGRSP/Mnsoil, CuGRSP/Cusoil and PbGRSP/Pbsoil) Against the

Log of their Contents in Soil.

Table 4. Correlation Matrix Among all Soil Parameters Obtained from all the Studied Soils.

Sand Silt Clay pH EC SOC EEGRSP TGRSP FeGRSP CuGRSP

Silt -0.925**

Clay -0.933** 0.726**

pH 0.074 -0.210 0.066

EC -0.019 0.194 -0.151 -0.716**

SOC -0.613* 0.633** 0.508* -0.389 -0.010

EEGRSP -0.130 0.221 0.025 -0.200 -0.242 0.658**

TGRSP -0.648** 0.498* 0.698** -0.217 -0.093 0.846** 0.421

FeGRSP -0.096 -0.032 0.201 -0.165 -0.371 0.697** 0.588* 0.778**

CuGRSP -0.009 0.038 -0.021 -0.205 -0.044 0.486 0.666** 0.559* 0.606*

NiGRSP -0.228 0.274 0.151 0.084 -0.251 0.141 0.224 0.062 -0.017 0.268

MnGRSP -0.581* 0.546* 0.530* -0.344 0.041 0.854** 0.288 0.728** 0.632** 0.303

PbGRSP -0.041 0.029 0.043 -0.419 -0.095 0.750** 0.616* 0.739** 0.895** 0.679**

Fe -0.246 -0.009 0.451 0.123 -0.442 0.491 0.188 0.692** 0.794** 0.267

Zn 0.228 -0.206 -0.218 -0.031 -0.158 0.151 0.557* 0.194 0.420 0.900**

Mn -0.659** 0.546* 0.674** -0.141 -0.211 0.866** 0.408 0.836** 0.711** 0.360

Cu -0.296 0.217 0.327 -0.231 -0.135 0.768** 0.561* 0.807** 0.861** 0.816**

Cd 0.198 -0.164 -0.203 -0.090 -0.085 0.186 0.543* 0.190 0.425 0.933**

Pb 0.036 -0.069 0.000 -0.126 -0.128 0.117 0.339 0.261 0.298 0.602*

Co 0.502* -0.438 -0.492 0.240 -0.396 -0.176 0.425 -0.349 0.108 0.199

Ni -0.504* 0.346 0.582* 0.148 -0.455 0.662** 0.209 0.734** 0.662** 0.197

Cr -0.421 0.186 0.582* -0.114 -0.121 0.574* 0.083 0.719** 0.714** 0.214

Table 4. Continued.

NiGRSP MnGRSP PbGRSP Fe Zn Mn Cu Cd Pb Co Ni

MnGRSP 0.100

PbGRSP 0.120 0.681**

Fe -0.079 0.612* 0.585*

Zn 0.215 -0.096 0.435 0.113

Mn 0.171 0.940** 0.661** 0.740** 0.006

Cu 0.131 0.712** 0.848** 0.706** 0.588* 0.768**

Cd 0.233 -0.019 0.462 0.095 0.984** 0.048 0.615*

Pb 0.205 -0.127 0.316 0.101 0.764** -0.021 0.435 0.700**

Co 0.379 -0.377 0.095 -0.056 0.347 -0.279 -0.068 0.315 0.138

Ni 0.182 0.763** 0.513* 0.839** -0.023 0.856** 0.668** -0.026 0.036 -0.124

Cr -0.103 0.742** 0.574* 0.832** -0.080 0.784** 0.649** -0.029 -0.100 -0.260 0.694**

** significant p-level <0.01, * significant p-level <0.05.

3.5. Factor Analysis

In Table 5, the first three factor structures, obtained from

Factor Analysis, explained 76% of total variance to represent

the most effective correlations among the analysed soil

properties (variables). Factor 1 explained 41% of total

variance with high positive loadings >0.60 from silt, clay,

SOC, TGRSP, Fe, Mn, Cu, Ni, Cr, FeGRSP, MnGRSP and

PbGRSP but negative loadings >0.70 only from sand. It is very

interesting to note that iron (Fe) and manganese (Mn) appear


to be sequestered by glomalin and potentially biostabilized

because of their significant positive correlation with TGRSP

(containing the more stable glomalin form) and SOC in the

soil. Factor 2 explained 21% of total variance with high

positive loadings from EEGRSP, Zn, Cu, Cd, Pb, FeGRSP,

CuGRSP and PbGRSP. The second factor showed that the labile

glomalin fraction (EEGRSP) was positively correlated with

Cu in soil and CuGRSP indicating its high potential

sequestration capacity with this metal. Despite that Zn in soil

was positively correlated with EEGRSP but the lower

concentrations found in all soils were not enough to represent

a clear trend of glomalin to sequester Zn from the soil. High

positive loadings from TGRSP and PbGRSP in Factor 1 and

from EEGRSP and PbGRSP in Factor 2 may indicate that

glomalin is predominantly bound to lead with a capacity to

reduce its bioavailability in soil [16]. The third factor

explained 14% of the total variance with high positive

loadings from pH against electrical conductivity. The total

communality values emphasized that Fe, Cu and Mn are the

main soil micronutrients predominantly bind to glomalin

with a potential of biostabilisation in the soil.

The factor score values were calculated to detect which soil

may positively or negatively contribute to each factor (Figure

5). Score values relevant to Factor 1 showed a positive

contribution from S8-S12 soils while the negative contribution

from other soils because of the large manure addition in the

former soils. Score values of Factor 2 showed the positive

contribution from S4, S6 and S8-S12 soils relatively associated

with the high positive loadings found in Factor 1 and 2. The

plot diagram in Figure 5 may summarize the relationships

among soils and variables loadings in the orthogonal space

defined by the first two Factors (1 and 2) in order to better

explain the dynamics of SOM and glomalin to bind metals.

The progressive shift from S1 to S16 along Factor 1 represents

a valuable indication of glomalin (TGRSP) to sequester Mn,

Fe and Cu, respectively, depending on their availability in soil.

This trend was clearly observed in S8-S12 soils. Delimited

squares may display the distribution of each metal along the

orthogonal space defined by the two Factors.

Table 5. Variable Loadings from the First Three Factor Structures with the

Communality Values Obtained by Factor Analysis.

Variables Factor 1 Factor 2 Factor 3 Communalities

Sand -0.79 0.70

Silt 0.65 0.58

Clay 0.81 0.71

pH 0.80 0.74

EC -0.95 0.93

SOC 0.83 0.87

EEGRSP

0.71 0.57

TGRSP 0.87

0.87

Fe 0.69 0.76

Zn 0.92 0.88

Mn 0.95 0.96

Cu 0.65 0.72 0.95

Cd 0.92 0.86

Pb 0.69 0.48

Co 0.58

Ni 0.83 0.87

Cr 0.81 0.68

GRSP-bound

metals

FeGRSP 0.59 0.64 0.84

CuGRSP 0.93 0.91

NiGRSP 0.08

MnGRSP 0.91 0.86

PbGRSP 0.62 0.72 0.79

Explained

Variance (%) 41 21 14

Cumulative

variance (%) 41 62 76 76

EC: Electrical conductivity; SOC: Soil organic carbon; EEGRSP: Easily

extractable glomalin-related soil protein; TGRSP: Total glomalin-related soil

protein. Values below 0.60 are deleted.

Figure 5. Plotting the Factor Loadings and Score Values of Factor 1 and Factor 2.


4. Conclusion

The GRSP-bound metals have been identified in this study

as FeGRSP, ZnGRSP, MnGRSP, CuGRSP, NiGRSP, and PbGRSP for

their abundance in the glomalin extracts and were

significantly correlated with their availability in soil. Iron,

manganese, copper and nickel were highly sequestered by

glomalin in those salt-affected soils (S4 and S8-S12) with

moderately alkaline conditions due to the intercropping with

legumes and receiving annual manure additions. Zinc was

highly sequestered by glomalin in S4 soil under apple trees

that sometimes receive Zn in its soluble form for promoting

plant growth. Despite that, glomalin resulted in the ability to

lower the toxicity of lead in soils. As a result, glomalin can

be used as a biotechnological tool of phytoremediation to

recover polluted soils. Further studies became paramount to

identify the structural components in each GRSP fraction to

better understand the glomalin sustainability under different

agricultural management.

Acknowledgements

We are grateful to thank Prof Dr Sionhán Staunton, INRA,

France for her helpful revision of this manuscript.

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Increasing Soil Nutrients Availability and Sustainability by ...article.aascit.org/file/pdf/8050014.pdfgrowth. Glomalin is a mycorrhizal glycoprotein produced in soil with the ability